MIT Sloan School of Management
|
|
- Neal Sparks
- 5 years ago
- Views:
Transcription
1 MIT Sloan School of Management Working Paper September 2002 Reporting Conservatism, Loss Reversals, and Earnings-based Valuation Peter R. Joos, George A. Plesko 2002 by Peter R. Joos, George A. Plesko. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission, provided that full credit including notice is given to the source. This paper also can be downloaded without charge from the Social Science Research Network Electronic Paper Collection:
2 Reporting Conservatism, Loss Reversals, and Earnings-based Valuation * Peter Joos and George A. Plesko Draft 1: January 15, 2002 This version: September 1, 2002 Abstract We study the determinants of losses and their increased frequency over time to understand their implications for the use of financial statements in valuation. We find the properties of losses change between both in terms of the cash flow and accruals components. Departing from prior research, we explicitly model the estimated likelihood of loss reversal. We find firms estimated to be least likely to reverse have unusually large negative cash flows and accruals, comprised of relatively large amounts of R&D expenditures and Special Items. We also find the market assesses both the effect of reporting conservatism and the attractiveness of abandoning the investment in the firm when it prices losses. We interpret this as evidence that the probability of loss reversal summarizes financial information useful to investors and serves as a proxy for the earning power of assets when the firm reports a loss.. JEL classification:m41; D21; Keywords: earnings; losses; conservatism; cash flows; accruals Contact information: Sloan School of Management Massachusetts Institute of Technology E52-325, 50 Memorial Drive Cambridge, MA Joos: , pjoos@mit.edu Plesko: , gplesko@mit.edu (corresponding author) * We thank SP Kothari, Joe Weber, Peter Wysocki and the participants of the accounting workshop at the Massachusetts Institute of Technology and the EAA 2002 Meeting in Copenhagen for helpful comments on an earlier draft.
3 Reporting Conservatism, Loss Reversals, and Earnings-based Valuation * Abstract We study the determinants of losses and their increased frequency over time to understand their implications for the use of financial statements in valuation. We find the properties of losses change between both in terms of the cash flow and accruals components. Departing from prior research, we explicitly model the estimated likelihood of loss reversal. We find firms estimated to be least likely to reverse have unusually large negative cash flows and accruals, comprised of relatively large amounts of R&D expenditures and Special Items. We also find the market assesses both the effect of reporting conservatism and the attractiveness of abandoning the investment in the firm when it prices losses. We interpret this as evidence that the probability of loss reversal summarizes financial information useful to investors and serves as a proxy for the earning power of assets when the firm reports a loss. 2
4 I. Introduction The number of firms reporting negative earnings (i.e., loss firms) has markedly increased over the last three decades. In the 1990s loss observations constitute about 35% of the US firmyears covered by the Standard & Poor Compustat database whereas they represent only about 15% of observations in the 1970s. Paradoxically, the increase in the frequency of accounting losses occurs as the US stock market rises to historically high levels. The divergence between these trends raises the questions of what drives the increase in the occurrence of loss observations and how investors value them. The questions are important since academics and other users of financial statements reserve a prominent role for accounting earnings in different decision contexts (see Watts and Zimmerman 1986). Focusing on firm valuation in particular, Modigliani and Miller (1966) discuss in their seminal paper how accounting earnings are a proxy for the expected and unobservable earning power of the firm s assets. However, they also note that negative earnings (i.e., losses) complicate the use of earnings-based valuation models since a loss impairs the ability of accounting earnings to be a proxy for a firm s assets unobservable earnings power in valuation models. Consequently, the increase in the frequency of losses poses a considerable challenge for users of financial statements because of the need to consider other (accounting) proxies for the earning power of assets to value the firm. We study the determinants of losses and their increased frequency over time to understand their implications for the use of financial statements in valuation. As our starting point, we focus on the relation between increased reporting conservatism in the US, the decline in cross-sectional firm profitability, and increased frequency of losses observed by Givoly and Hayn (2000). An increase in reporting conservatism implies a change in the structural relation 1
5 between earnings, accruals, and cash flows (Givoly and Hayn 2000, p. 289). Consequently we hypothesize that if more losses occur as a result of increased reporting conservatism the implications of a current loss for the valuation of the firm change. We differentiate our research design from earlier studies (e.g., Basu 1997, Givoly and Hayn 2000) by adopting a broader notion of reporting conservatism. Although previous authors do not provide a unique definition of reporting conservatism, they typically relate the concept to the measurement of accruals. In contrast, we also consider the impact of structural changes in the nature of business operations, such as an increase in the investments in intangibles and R&D expenditures in particular, on the properties of losses and their implications for valuation. Whereas R&D investment does not generate negative accruals, its accounting treatment is conservative. The increase in the relative level of R&D investments during recent decades (see for example Amir and Lev 1996; Lev and Zarowin 1999) therefore potentially influences the occurrence of losses, their properties, and their implications for valuation. We carry out two analyses to evaluate how increased conservatism affects the frequency and properties of losses. First, we investigate whether the characteristics of loss firms change over time consistent with increased reporting conservatism. Second, we study whether the probability of a firm s return to profitability (i.e., loss reversal) changes over time consistent with the effect of increased reporting conservatism. We focus on loss reversals because a loss places the firm in a temporary position: the firm s return to profitability is the maintained hypothesis of financial reporting, embodied in the going concern assumption. Similarly, loss reversal forms the basis of the abandonment option view of loss valuation: shareholders have the option to redeploy or liquidate the assets of the firm when the firm continues to incur losses (Hayn 1995; 2
6 Berger et al. 1996; Wysocki 2001). We assume the length of time the firm needs to reverse a loss and the actions the firm takes to reverse relate to three generic categories of variables that capture the business environment and operations of the firm: 1) variables that describe the loss history of the firm; 2) variables that measure the financial profile of the firm; 3) variables that capture the dividend paying behavior of the firm. We predict increased reporting conservatism will affect the ability of particular variables to predict loss reversals. We test our predictions in a sample of loss observations from 1971 to We evaluate the effects of increased reporting conservatism on the properties of losses by splitting our sample in time: a first subsample covering 1971 through 1990 and a second covering the years 1991 through We find the properties of losses change between the sample periods in terms of the cash flow and accruals components of losses. When we estimate our model of loss reversal probability we find the pattern of results is consistent with increased reporting conservatism having an effect on the properties of losses and loss reversals. The loss history variables show on the one hand that first-time losses are more likely to reverse during the later period ( ) than during the earlier period ( ), indicating that losses have become more transitory over time. On the other hand, we find firms with multiple losses have become less likely to return to profitability in the later period: accounting loss sequences appear to persist in recent years potentially as a result of the greater use of conservative accounting methods. Focusing on the other financial statement variables in the reversal model, we find corroborating evidence of an increasing influence of long-term accruals on losses and their reversal. In further analysis, we find the earnings of firms with the lowest probability of loss reversal have unusually large negative cash flows and accruals, establishing that accruals 3
7 differences across loss firms do not solely determine our estimated likelihood of loss reversal. We also find firms with the lowest probability of loss reversal record larger amounts of R&D expenditures and Special Items than other firms, a pattern that becomes more pronounced during the period. We argue that R&D and Special Items capture changes in business operations that are reported conservatively, leading to more negative cash flows and/or accruals. Next we investigate whether market participants change their interpretation of losses for firm valuation consistent with changes in their properties. We estimate earnings response coefficients (ERC) for loss observations in the full sample and find no relation between losses and stock returns in the early sample period, consistent with losses being a poor proxy of the earning power of assets. In contrast, in the later period we find a significant negative relation between losses and returns. In further analysis, we establish that firms with the lowest probability of loss reversal drive the result in the full sample and that firms with a higher probability of loss reversal still exhibit no relation between returns and losses. When we redefine earnings to exclude R&D and Special Items we find the negative earnings response coefficient for observations with the lowest reversal probabilities disappears. Also, the redefined earnings of firms with higher probabilities of loss reversal exhibit a positive and statistically significant relation with returns, especially in recent years. Taken together, our evidence suggests not only that investors acknowledge the existence of conservative components when they price losses, but also that investors price losses consistent with the probability of loss reversal serving as a proxy for the earning power of assets. Our study extends the literature on the effects of reporting conservatism on the use and implications of financial statements. Focusing on losses in particular, we show the properties 4
8 and implications of losses for valuation change consistent with effects of increased reporting conservatism. As a central part of our analysis we model and estimate the process of loss reversal. Whereas previous research identifies variables that help to predict bankruptcy (e.g., Altman 1968), surprisingly little is known about what variables help to predict loss reversal of firms. We believe the practical relevance of the prediction of loss reversal has become more important given the increased frequency of losses for a large cross-section of firms. We show the loss histories of the firm along with contemporaneous financial information help to predict the firm s return to profitability in the near future. We also document that the role and importance of the variables in our empirical model change over the sample period consistent with increased reporting conservatism over the sample period. We contribute to the valuation literature by showing how the probability of loss reversal relates to the pricing of losses: in addition to taking into account particular conservative components of losses the market values earnings of loss firms differently depending upon the expected probability of loss reversal. Our finding contributes to a better understanding of the role of the abandonment option in valuation (see also Hayn 1995). Given two otherwise identical firms, differences in the probability of reversal indicate differences in the earning power of assets of the firm and the attractiveness of abandonment and therefore affect how investors price losses. In the next section we describe our sample and document the significance of loss firms in the economy and the aggregate patterns of loss duration. In Section III we investigate the properties of loss observations in our sample and describe and estimate our model of loss reversals. In Section IV we evaluate whether investors valuation of earnings is consistent with 5
9 the changing properties of losses. In the final section we summarize our results. II. The Prevalence and Duration of Losses We obtain a sample of loss firms from Compustat s Industrial and Research Annual Data Bases for the period Consistent with Hayn (1995) we define our earnings variable as income (loss) before extra-ordinary items and discontinued operations or IB (annual Compustat data item #18). Our initial sample contains 217,085 firm-year observations. Table 1 presents descriptive statistics on the prevalence of losses in our sample. We report statistics for both our main earnings variable of interest, IB, and for bottom-line earnings or net income NI (annual Compustat data item #172). Panel A shows the sample contains 29.63% loss observations. Similar to Table 1 in Hayn (1995) we find the number of loss observations increases over time, an pattern that continues to 2000 in our extended sample. We summarize the yearly lossfrequencies per decade and find that in the 1970s about 15% of earnings observations are losses. This percentage increases in the 1990s to about 36% (for both IB and NI). In Panel B of Table 1, we document the distribution of the number of years with losses based on a sample of firms with at least 7 years of observations. This criterion allows us to study loss history over a longer window for a subset of firms in a later analysis. 1 Focusing on IB, panel B shows 27.21% of the firms in our sample never incur a loss over the period studied. In contrast, about 10% of firms incur more than 10 losses over this 30-year period. Similar to panel B, panel C shows the distribution of the number of years with losses, but now based on a sample of 885 firms with 30 years of observations (i.e., the complete sample period). We find about 6
10 one-third of firms never incur a loss during the sample period. However, more than 7% of this sample has more than 10 losses over the entire period. The results in panels B and C are similar for NI. The results in panels B and C of Table 1 show losses can persist for a considerable time, motivating us to explore the determinants of the losses and the market s valuation of information other than earnings in the case of losses. As a first step, we explore in Table 2 how a firm s return to profitability varies as a function of the recent loss history of the firm. In panel A, we document how reversal one year into the future varies as a function of the length of the past sequence of losses. We find that of firms experiencing their first loss (i.e., the sequence is 1 year long) 45.47% are profitable in the next year. The percentage changes drastically as a function of the past history of losses. Of firms suffering two consecutive losses, only 34.76% reverse to a profit the next year. The reversal probability monotonically decreases to 27.55% for firms with 5 sequential losses. Panel B documents how reversal over the following five years varies as a function of the past sequence of losses. This analysis reduces the number of observations as it imposes substantial restrictions on our dataset, requiring 10 consecutive observations for each loss firm (the current year observation, 4 past observations and 5 future observations). We find that for 6,983 firm-year observations where the current loss is the first in a (potential) sequence, 46.79% of observations are profitable again one year into the future, and 11.6 percent do not reverse within 5 years. For the companies that do not reverse in the next year, the conditional probability of reversing in subsequent years declines monotonically, from 36.77% after two losses to 31.88% after 5 years. In each column of the table, we find a pattern similar to the rows. 1 To mitigate possible effects of survivorship bias we code a firm as non-reversing if it is dropped from the 7
11 The relative magnitude of the reversal percentages, however, varies considerably as a function of the length of the loss sequence of the firm across the columns of the table. For example, in the last column, comprised of 621 firms where the current loss is the fifth in the sequence, less than a third reverse the following year and about a quarter of the observations do not reverse at all over the 5-year horizon. Taken together, the descriptive evidence in Table 2 suggests loss reversals follow a distinct pattern conditional on the number of losses already experienced. Interestingly, the longer the loss sequence of the firm, the lower the probability the current loss will reverse in the future, presenting particular challenges for fundamental analysis and/or valuation of the firm. In the next section we examine the characteristics of loss observations. III. Properties of losses We observe earlier the increased incidence of losses over the last three decades at a time when the US stock market rises to historically high levels. In this section we examine whether the characteristics of losses have changed over the sample period as the divergence between the trends in accounting earnings and market valuations suggests. We link our investigation to the accounting literature that studies increased reporting conservatism over the past decades (e.g., Givoly and Hayn 2000). In particular, we start by examining if the cash flow and accrual components of the loss observations in our sample change over time. Next, we develop an empirical model of loss reversals. The focus on loss reversal is a central feature of our analysis because previous research argues shareholders do not expect losses to persist since they have the Compustat Annual File due to bankruptcy or liquidation but still appears in the Research File. 8
12 option to redeploy or liquidate (abandon) the assets of the firm (see Hayn, 1995; Berger et al. 1996; Wysocki 2001). A current loss therefore complicates the evaluation of the firm s future to the extent there exists uncertainty about its potential reversal. We model loss reversal to assess how investors use financial information to value loss firms when the loss impairs the ability of earnings to serve as a proxy for the earning power of assets. Finally, we explore the properties of losses as a function of the estimated probability of loss reversal. As a first exploration of the relation between reporting conservatism and the properties of losses, we document the cash flow and accrual components of the loss observations in our sample in Table 3. As a reminder, we evaluate the effects of increased reporting conservatism on the properties of losses by splitting our sample into two subsamples: a first subsample covering 1971 through 1990 and a second covering 1991 through We define CFO_SALES as cash flow from operations scaled by sales (annual Compustat data item # 12). Consistent with previous literature (Hayn 1995), we measure cash flow from operations as net income (annual Compustat data item # 172) accruals, where we measure accruals as ( Current Assets (data item #4) - Cash (data item #1) - Current Liabilities (data item #5) + Debt in Current Liabilities (data item #34) + Depreciation and Amortizations (data item #14). ACC_SALES is accruals (as defined before) scaled by sales (annual Compustat data item # 12). Panel A of Table 3 shows that in the full sample the means and medians of the cash flow and accrual components of losses are negative. We further observe a marked difference between the means of the variables across the subperiods: both the means and medians of the cash flow and the accrual component become significantly more negative (significant at the 5% level for cash flows and the 10% level for accruals), consistent with increased conservatism. 9
13 In panel B we use perfect foresight to distinguish between loss observations that return to profitability the following year and those that do not. We observe the means and medians of both cash flow and accrual components of non-reversing firms are more negative than their counterparts in the reversal subsample, suggesting firms that do not return to profitability suffer larger losses on average. We also document the deterioration of the cash flow and accrual components presented in panel A primarily occurs in the non-reversing sample. In the nonreversing sample, the means and medians of both loss components are significantly more negative in the later subperiod. In the reversal subsample, the differences between the means and medians across time periods are still negative but no longer statistically significant. The pattern of results therefore confirms that the characteristics of losses change over time. Interestingly, the change is more pronounced for the cash flow component than for the accruals component of the losses. Also, as panel B shows, the changing characteristics of losses relate to a firm s return to profitability the following year. Next, we estimate models of loss reversal to assess if the characteristics of losses change over our sample period. Our descriptive results in Tables 1 and 2 show losses can persist for a number of years, i.e., reversals do not always take place in the immediate future. The eventual reversal, however, and the ability to maintain operations until that eventual reversal are a necessary condition for long-term profitability. We assume the length of time the firm needs to reverse the loss, and the actions the firm takes to reverse its position are related to the business environment and operations of the firm. We develop and employ an empirical model based on factors that capture aspects of the business environment and operations of the firm to estimate the likelihood of the firm s return to profitability one year in the future. 10
14 We focus on loss reversal one year into the future because the results in panel B of Table 2 show that regardless of the number of losses the firm has experienced, the unconditional probability of reversal is always highest in the next year. We model the year ahead reversal of losses by estimating the following model: y t+1 = X t b + ε t+1 (1) where y t+1 is an indicator variable equal to one if the firm becomes profitable in the subsequent period, and zero otherwise, X t represents the information variables of the model, and ε t+1 is an error term. If a variable predicts an increased likelihood of loss reversal then the sign of its coefficient will be positive. In the absence of a formal theory of loss reversals, we consider several different types of information variables in our model. The first set of variables capture the firm's past loss history. We include these variables in the model since the results in panels B and C of Table 2 suggest loss reversal is related to the sequence of past losses. We measure both the incidence and the relative magnitude of past losses. Specifically, we consider the following variables: FIRSTLOSS is an indicator equal to one if this year's loss is the first in a sequence (i.e., the firm was profitable the previous year) and zero otherwise; NUMLOSS is an indicator variable equal to one if the firm incurred more than two losses in the past five years and zero otherwise; and finally, MAGNLOSS3 is an indicator variable equal to one if the sum of the current loss and the past three earnings numbers is negative and zero otherwise. Based on the patterns observed in Table 2, we expect the coefficient on FIRSTLOSS will be positive: if the current loss is the first in a sequence, the probability of loss reversal is higher relative to other loss firms. Similarly, we expect the coefficient on NUMLOSS to be negative: 11
15 the more losses the firm has incurred, the smaller the probability the loss will reverse in the next period. MAGNLOSS3 captures whether the current loss is large relative to the cumulative earnings of the past three years. We predict a negative coefficient on MAGNLOSS3 since MAGNLOSS3 is one if the current loss is larger than the cumulative amount of income of the past three years. This would indicate the firm has relatively greater difficulty sustaining profitability. To capture other financial information beyond loss history we select a second set of variables to capture demographics and past profitability of the firm. First, we include SIZE, measured as the log of current market value (annual Compustat data item # 199 * annual Compustat data item # 25). We expect this coefficient to be positive, consistent with large firms being financially stronger than small firms and therefore able to return to profitability more easily. The second variable, return-on-assets (ROA) is measured as income before extra-ordinary items (annual Compustat data item # 18) scaled by lagged total assets (annual Compustat data item # 6). Since all firms in our sample will have negative ROA in the current year, we predict a positive sign for ROA as firms with less negative ROAs will be more likely to return to profitability. The next variable, NEGCEQ, is an indicator variable equal to one if the firm has negative equity (annual Compustat data item # 60) and zero otherwise. NEGCEQ captures cumulative profitability. We interpret the occurrence of negative equity as an indication that the profitability problems of the firm are substantial, and predict a negative coefficient on this variable. We also include recent growth in sales, SALESGROWTH, measured as the percentage growth in sales (annual Compustat data item # 12) during the current year. Although we expect sales growth to signal a pending return to profitability, the effect of sales growth on the 12
16 probability of loss reversal is weakened if high sales growth identifies young firms in the sample that have not yet achieved profitability. Relatively young firms can remain unprofitable for a number of years during the early stages of their life and therefore sales growth will not be a good predictor of loss reversals. 2 We expect long-term accruals will also influence losses and loss reversal. For example, if a firm has been active in takeovers accounted for as purchases the earnings number is likely influenced by goodwill amortization. We therefore include a profitability measure in the model unaffected by these accruals, namely EBITDA. We measure our variable EBITDA_SALES as operating income before depreciation (annual Compustat data item # 13), scaled by sales (annual Compustat data item # 12). The predictive power of EBITDA_SALES for loss reversals depends on whether the current loss is caused by real operational problems or by accounting choices. We predict that higher (or less negative) values of EBITDA_SALES will be associated with a higher probability of loss reversal. 3 Finally, we include two variables that capture the dividend paying behavior of the firm. Following Healy and Palepu (1988), who show management signals profitability changes through dividend changes, we consider that management potentially signals upcoming loss reversals similarly. We include DIVDUM, an indicator variable equal to one if the firm is paying dividends (annual Compustat data item # 21) and zero otherwise. We predict that if a firm continues to pay dividends while incurring losses it signals the loss sequence is expected to be relatively brief. As a result we predict a positive coefficient on DIVDUM. We also include 2 Notice that we require each observation in the sample to have a history of five years of data. As a result, our sample does not include recent IPOs. 13
17 DIVSTOP, an indicator variable equal to one if a firm stopped paying dividends in the current year and zero otherwise. We predict that if a firm stops paying dividends this year because its financial situation is deteriorating rapidly the coefficient on this variable will be negative. We estimate equation (1) annually to investigate whether the nature of losses and the loss reversal process changed over our sample period. To document the change we average the results over the two subperiods earlier defined. Before presenting the results of the model estimation, we discuss descriptive statistics for the variables included in the logistic regression (1) in Table 4. Panel A presents descriptive results for the six indicator variables defined earlier, conditional on whether the loss reverses or not. Focusing on the three loss variables, the results are consistent with our expectations. We observe that in the full sample the occurrence of a first loss is significantly associated with loss reversal: when the current loss is the first in a sequence (i.e., FIRSTLOSS is 1) 45.57% percent of firms experience loss reversal as opposed to 26.17% when the current loss occurs after a previous loss. Focusing on NUMLOSS, we see the probability of loss reversal is significantly smaller (23.55% vs %) if the firm has experienced more than two losses in the last five years, i.e., NUMLOSS is 1. Finally, if the sum of the past three years of earnings is not larger than the current loss (i.e., MAGNLOSS3 is 1) the probability of reversal is also smaller than if the sum is larger (27.68% vs %). We also observe that the divergence between the percentages of reversals and no reversals widens in the later subperiod, suggesting the process of loss reversal as a function of the past history of losses changes. 3 We also estimated our model with both a cash flow and an accruals variable include in lieu of EBITDA. The results remain qualitatively unchanged. 14
18 The panel further documents that negative equity (i.e., NEGCEQ is 1) is statistically related to the probability of loss reversal. Current loss firms with negative equity become profitable in only 22.43% of the cases, compared to 35.32% for positive equity firms. The percentage of reversals conditional on negative equity declines in the later subperiod, consistent with a prolonged lack of profitability being more cosmetic in nature in this period. The dividend variable DIVDUM also relates significantly to the probability of loss reversal. The probability of loss reversal in the full sample for a current loss firm that pays dividends is 53.49% compared to 29.94% for firms that do not pay dividends. The results for the subperiod samples show this divergence widens in the later subperiod. Finally, all results for the DIVSTOP variable are insignificant. Panel B provides descriptive statistics for the continuous variables defined earlier in the full sample and the two subperiod samples and shows the distributions of the variables differ across the two subperiods. In particular, the average size of loss firms increases over the sample period. Average ROA is negative by default and decreases in the later period. Similarly, EBITDA_SALES, also negative on average, decreases sharply over time. In contrast, SALESGROWTH is higher in the later period. All differences between means and medians of the two subperiod samples are significant at the 5% (with the exception of the differences between the mean and median of SALESGROWTH). Panel C provides descriptive statistics for the continuous variables conditional on whether the firm becomes profitable the following year. We find reversing firms to be larger with higher (i.e., less negative) ROAs, SALESGROWTH, and EBITDA_SALES than firms that do not reverse. Unreported analyses show all mean and median differences between the reversal 15
19 and no reversal samples are significant, with the exception of those of SALESGROWTH. Finally, we also find the pattern of panel A reflected in the reversal and no reversal subsamples. Similar to the results in panel B of Table 3, the time period changes are more pronounced in the no reversal sample, suggesting again that the characteristics of loss firms change over time related to their chances of becoming profitable the next year. Table 5 presents the results of the logistic regression (1). The table reports the coefficients and associated t-statistics computed for the entire sample, and separately for each of the two subperiods following the procedure in Fama-MacBeth (1973). Since Table 3 demonstrates a shift in the nature of losses occurring between the two subperiods we focus our discussion of the results primarily on the two subperiod models and report the results for the full sample as a benchmark. In addition to the average coefficient estimates, we also present the estimated average marginal effects of each variable in the model. We measure the marginal effect as the change in the estimated probability of reversal given a local change in the value of the independent variable, evaluated at the sample mean for all variables (with indicator variables set equal to zero). The marginal effect of an indicator variable measures the effect on the probability of reversal caused by a change in the variable from 0 to 1. Examining the results for we find two of the three loss history variables are highly significant. Firms experiencing their first loss (FIRSTLOSS) are estimated to have a 4.1 percent higher probability of reversal than other firms. Also, firms with a current loss greater than the sum of the past three years income (MAGNLOSS3) are estimated to be 9.7 percent less likely to reverse. The effect of NUMLOSS on the probability of reversal in this period is less 16
20 pronounced. While the coefficient estimate is negative for firms that experienced more than two losses in the past five years, it is not statistically significant. The coefficients on SIZE, EBITDA_SALES and DIVDUM are positive and statistically significant, as expected. EBITDA_SALES also displays a large marginal effect on the probability of loss reversal (10.4%). In contrast, firms with negative equity (NEGCEQ) are less likely to reverse to profitability. The coefficient on NEGCEQ is statistically significant, with these firms estimated to be 4.3 percent less likely to reverse than similar positive equity firms. Finally, the coefficients on DIVSTOP, ROA and SALESGROWTH are not statistically significant. For the sample the model s fit increases measured by either the percentage of firms correctly classified or the pseudo-r 2. Apart from the insignificant coefficients on SALESGROWTH, none of the coefficient estimates changes in sign. Some, however, change in magnitude and significance. The coefficient on FIRSTLOSS increases (from to 0.366) with a slight increase in the marginal effect from 4.1 percent to 5.0 percent. Further, the coefficient on NUMLOSS is now statistically significant with an estimated marginal effect of 7.6 percent, more than tenfold the point estimate for the first period. Firms with large losses (MAGNLOSS3) are still estimated to be less likely to reverse (i.e., the coefficient is still negative and significant), however the effect of large loses on the marginal effect decreases from 9.7 percent to 4.6 percent. The coefficients on and the marginal effects of SIZE and SALESGROWTH remain essentially the same over the periods. We observe a change in importance in the model of ROA in the second subperiod: the coefficient increases from to 0.689, is significant, and the marginal effect on the probability of reversal increases to 12.3%. In contrast, the influence of both NEGCEQ and EBITDA_SALES on the probability of reversal 17
21 decreases, with the marginal effect on the probability of reversal of EBITDA_SALES decreasing from 10.4% to 1.4%. Finally, while DIVSTOP remains insignificant the effect of DIVDUM on the probability of reversal increases: the coefficient increases from to and the marginal effect doubles to 8.1% from 4.0%. In sum, the results of the logistic regression model in Table 5 confirm that the properties of losses and loss reversals change over time. In particular, the results for the loss history variables suggest that losses not only become more prevalent in the 1990s, the change in influence of NUMLOSS across the subperiods also indicates the probability of reversal given a series of losses falls dramatically: firms are able to remain unprofitable for longer periods without reversing back to profitability. The increased influence of the FIRSTLOSS variable combined with the decreased influence of the magnitude of the current loss further suggest that more big bath type losses occur in the second subperiod from which firms more easily return to profitability. The most important change in the financial profile variables relates to EBITDA_SALES: an improvement in EBITDA_SALES contributes considerably less to the probability of reversal in the second subperiod, a result consistent with an increasing influence of long-term accruals on losses and their reversal. We argue before that our probability model of loss reversal summarizes financial information investors can use to assess the earnings power of assets of the firm in the case of losses. We next explore in more detail if firm characteristics vary as a function of the estimated probabilities of reversal consistent with this argument. We focus specifically on characteristics of losses related to reporting conservatism since we find evidence in our earlier analysis that increased reporting conservatism potentially influences the properties of losses. Table 6 contains 18
22 the results of the analysis with observations sorted into quartiles based on their estimated probability of reversal (observations with the lowest estimated probability are in quartile 1). First we document in panel A that the mean (median) probability of reversal decreases between subperiods from 0.36 (0.34) for to 0.33 (0.30) for ; a pattern we observe across subperiods in the first three quartiles but not in the fourth. In panel B we provide details on the cash flow (CFO_SALES) and accruals (ACC_SALES) components of losses by quartile for each of the periods. We find that regardless of the period, cash flows are lowest (i.e., most negative) for firms with the lowest reversal probability and monotonically increase with the probability of reversal. Notice how the largest change between the two periods occurs in quartile 1 where mean cash flows fall from to Overall, with the exception of quartile 3, mean and median CFO_SALES are lower in the later period than in the earlier. Accruals follow a similar pattern. Overall, mean and median accruals stay constant or decline across subperiods with the largest decrease between the subperiods taking place in quartile 1. These patterns extend the evidence on the patterns of cash flows and accruals described in Table 3. Panel B in Table 6 shows the losses of firms least likely to return to profitability in the following year drive the statistically significant differences in mean cash flows and accruals observed over the two periods in Table 3. Consistent with Table 3, we find the declines in cash flow between subperiods to be much larger than the declines in accruals, contradicting that reporting conservatism with respect to accruals alone is responsible for the changing nature of losses in recent years (see also Givoly and Hayn 2000). To explore further what distinguishes firms as a function of their estimated probability of loss reversal we study the influence of two particular accounting items on the characteristics of 19
23 losses in more detail, namely R&D expense and Special Items. We focus on R&D since we adopt a broader definition of reporting conservatism than in related research by including the effects of structural changes in the nature of business operations. Recent research finds investments in intangibles, and in R&D in particular, has increased significantly over the past decades and has influenced the properties of reported accounting measures (e.g., Amir and Lev 1996, Collins et al. 1997, Lev and Zarowin 1999). Although R&D investment does not generate negative accruals, the immediate expensing of R&D investments is conservative and potentially influences the occurrence and properties of losses. In addition, we examine the specific influence of Special Items on the properties of losses since Special Items should only have a temporary effect on earnings, and reduce the short-term ability of earnings to measure performance (Dechow 1994). Recent research on reporting conservatism and losses also focuses on Special Items since negative Special Items related to restructurings and write-offs typically lower reported earnings through negative accruals (Givoly and Hayn 2000, p. 305). Particularly relevant for our focus on loss reversals are the findings in Carter (2000) and Burgstahler et al. (2002) which conclude that negative Special Items represent inter-period transfers that lead to increased earnings in subsequent periods. Carter (2000) in particular shows that the postrestructuring performance of firms is greater than the upward bias caused by the accelerated recognition of Special Item restructuring expenses. In other words, the presence of Special Items could have a particular impact on the properties of losses and their subsequent reversal. We examine the R&D and Special Items components of losses in panel C of Table 6. We scale both components by sales to allow cross-sectional comparisons. We find that R&D as a percentage of sales increases in the second subperiod in all but quartile 3. The most pronounced 20
24 increase occurs in quartile 1, where mean R&D expenditures go from 0.43 percent of sales to 2.68 percent, an increase of more than 500 percent. Notice also that quartile 2 firms report a mean increase of R&D of 300 percent between the two periods. The panel further shows that across all quartiles Special Items become more negative during than Again the average effect is most pronounced in quartile 1, where mean Special Item charges increase from 0.13 to 0.81 percent of sales. The change in quartile 1 is less pronounced in terms of median Special Items; the medians change only in quartiles 3 and 4 going from zero to 0.01 and 0.02, respectively. Our finding that firms with the lowest reversal probability report more negative Special Items on average contrasts with the evidence in Burgstahler et al. (2002) that negative Special Items relate to positive earnings changes. However, positive earnings changes are a necessary but not a sufficient condition for loss firms to become profitable; our research design therefore examines a stricter criterion. Summarizing, we conclude based on the evidence in Tables 3 through 6 that the characteristics of losses change significantly over the past 30 years, consistent with claims of increased reporting conservatism. Losses become more prevalent in the 1990s and firms are able to remain unprofitable for longer periods without reversing back to profitability. We also document the reporting conservatism relates to accruals and cash flows: we observe a steep increase in the R&D investment as a percentage of sales in recent years for loss firms, particularly for those observations that obtain a low estimated probability of a return to profitability in the following year. 21
25 IV. The valuation of losses: earnings response coefficients After showing how the characteristics of loss firms change over the last three decades, we now turn to the question of whether investors price losses differently over time as a result of the change. Earlier research on the valuation of loss firms considers the role of the abandonment option for the value-implications of losses. For example, Hayn (1995) explains how investors consideration of the abandonment option explains the lower earnings response coefficients (ERCs) in large sample studies in the presence of losses. Burgstahler and Dichev (1997), Collins et al. (1997) and Collins et al. (1999) also study firm valuation in the presence of losses and use book value as a proxy for the abandonment value of the firm. We extend the investigation of the valuation of losses starting from our earlier evidence that losses, coupled with other information, allow for explicit estimates of the need to abandon or liquidate an investment. We interpret the prediction of loss reversal as one particular way to structure financial information to assess the likelihood of abandoning an investment in the firm. Otherwise put, we assume the loss reversal probability provides information about the earning power of assets when the firm faces a loss. We carry out two analyses. First, we explore whether the market prices earnings consistent with the prediction of loss reversal. To do this, we investigate if ERCs of loss firms vary as a function of the probability of reversal. We estimate ERCs based on the following regression (see also Hayn 1995): Ret t = α + β IB t + ε t (2) where Ret t is the return over the 12-month period commencing with the fourth month of fiscal year t, IB t is the earnings per share variable in year t (annual Compustat data item #18 scaled by annual Compustat data item #25) scaled by P t-1 or share price (annual Compustat data item #199) 22
26 at the end of year t-1, ε t is the error term. Consistent with our annual estimation of the loss reversal model, we estimate equation (2) in each year of the sample period and assess the significance of the ERCs using the Fama-Macbeth procedure (1973). We estimate equation (2) in the full sample and in subsamples based on the quartiles of the annual distribution of the probability of reversal distribution to document the variation of the ERCs as a function of the likelihood of loss reversal. To assess if investors change the valuation of losses over time, we also distinguish between the earlier defined subperiods in our research design. Second, in light of the evidence in the previous section we also ask whether investors change the valuation of losses as a function of the change in the characteristics of the losses over time. Based on the results in panel C of Table 6, we redefine earnings to exclude the R&D and Special Items components and estimate ERCs based on the following regression: Ret t = α + β IBWO t + ε t (3) where IBWO t is earnings per share (annual Compustat data item #18 scaled by annual Compustat data item #25) in year t before R&D (annual Compustat data item #46) and Special Items (annual Compustat data item #17) scaled by P t-1 or share price (annual Compustat data item #199) at the end of year t-1; Ret t is as previously defined and ε t is an error term. By comparing the results of equation (2) and (3), we can assess if investors explicitly consider the changing nature of losses in valuation. Before turning to the results of the estimation of equations (2) and (3), we briefly discuss the variables of interest in the analysis in Table 7. Panels A and B provide descriptive statistics for returns (Ret) and earnings (IB), the dependent and independent variables in equation (2). Both panels show a marked difference in the distribution of these variables between the two 23
27 subperiods in our sample. Panel A reports that while the mean return for loss firms during was 0.05, with a median of 0.18, the mean return during was positive, 0.12, while the median return increases to The mean return of loss firms increases in all four quartiles between the two periods, with only quartile 4 (those firms estimated as most likely to reverse) having a negative mean return during Note also the means and medians of the full sample and the first two quartiles are significantly different across both subperiods. Panel B shows that regardless of the subperiod, mean and median net income increase monotonically with the estimated probability of reversal. With the exception of quartile 3, mean and medians increase in the full sample and in the separate quartiles across the two subperiods. Again, all differences between means and medians are significant in the entire sample and in the first two quartiles. Panel C contains descriptive statistics on the redefined earnings variable IBWO t or earnings per share excluding R&D and Special Items. Removing the effects of R&D and Special Items increases the mean earnings per share from 0.25 reported in panel B to for , and from 0.22 in panel B to 0.09 in , with almost no effect on the standard deviations. The median value of IBWO is also larger in both periods than the median of IB. Panel C also shows that, regardless of the time period, the pattern of IBWO across the four quartiles remains the same, with higher probability of reversal firms having higher mean IBWO. Finally, all means and medians increase in the second subperiod. Unreported analysis shows that removing R&D and Special Items from income reduces the number of firms with losses in the sample by 1,444 (25.0%) for the period and by 2,507 (32.3%) for the
28 period, consistent with these two components of losses becoming more important in the second subperiod. The descriptive evidence in Table 7 suggests the relation between returns and losses (defined as IB or IBWO) changes over the sample period in the full sample and in the quartile subsamples. Whereas the probability of reversal appears positively correlated with both earnings variables in both subperiods, the table shows firms with lower probabilities of reversal exhibit higher returns in the later subperiod but not in the earlier subperiod. Table 8 shows how the change affects the ERCs in the different samples. Panel A of Table 8 shows the result of the estimation of equation (2). We observe that in the estimated ERC in the full sample is 0.03 and statistically insignificant, similar to the statistically insignificant 0.01 ERC reported by Hayn (1995, Table 4) for loss firms. The lack of statistical significance carries through to each quartile in this subperiod. In contrast, when we estimate equation (2) in the subperiod, the ERC is and statistically significant, implying that larger losses yield higher returns. In analyzing the quartile regressions we find the result is driven entirely by the observations in quartile 1: the ERC in quartile 1 is also 0.17 and statistically significant while none of the other quartiles estimates are statistically significant. Panel C of Table 8 shows the differences between ERCs are statistically significant across the two subperiods in the full sample and in quartile 1. In contrast, the differences across the two periods are not statistically different in quartiles 2 to 4. Taken at face value, the results in panel A seem inconsistent with investors pricing losses as if they assess the probability of loss reversal or as if they consider the abandonment option when valuing the firm. Instead, it appears the market rewards the firms with the poorest 25
Core CFO and Future Performance. Abstract
Core CFO and Future Performance Rodrigo S. Verdi Sloan School of Management Massachusetts Institute of Technology 50 Memorial Drive E52-403A Cambridge, MA 02142 rverdi@mit.edu Abstract This paper investigates
More informationThe Reconciling Role of Earnings in Equity Valuation
The Reconciling Role of Earnings in Equity Valuation Bixia Xu Assistant Professor School of Business Wilfrid Laurier University Waterloo, Ontario, N2L 3C5 (519) 884-0710 ext. 2659; Fax: (519) 884.0201;
More informationMIT LIBRARIES .1, ma f" )\r'u, ii/i. i';ff ^itih f ^ I
I I MIT LIBRARIES 3 9080 02618 4603 '.1, ma f" )\r'u, i';ff ^itih f ^ I ii/i S3 no MM^*^'^^ DEWEY MIT Sloan School of Management MIT Sloan Working Paper 4474-04 January 2004 Costly Dividend Signaling:
More informationThe Separate Valuation Relevance of Earnings, Book Value and their Components in Profit and Loss Making Firms: UK Evidence
MPRA Munich Personal RePEc Archive The Separate Valuation Relevance of Earnings, Book Value and their Components in Profit and Loss Making Firms: UK Evidence S Akbar The University of Liverpool 2007 Online
More informationDo Investors Understand Loss Persistence?*
Do Investors Understand Loss Persistence?* Kevin Ke Li Haas School of Business University of California at Berkeley 545 Student Services #1900 Berkeley, CA 94720 kli@haas.berkeley.edu http://faculty.haas.berkeley.edu/kli/
More informationOnline Appendix to. The Value of Crowdsourced Earnings Forecasts
Online Appendix to The Value of Crowdsourced Earnings Forecasts This online appendix tabulates and discusses the results of robustness checks and supplementary analyses mentioned in the paper. A1. Estimating
More informationAsymmetries in the Persistence and Pricing of Cash Flows
Asymmetries in the Persistence and Pricing of Cash Flows Georgios Papanastasopoulos University of Piraeus, Department of Business Administration email: papanast@unipi.gr Asymmetries in the Persistence
More informationDiscussion Reactions to Dividend Changes Conditional on Earnings Quality
Discussion Reactions to Dividend Changes Conditional on Earnings Quality DORON NISSIM* Corporate disclosures are an important source of information for investors. Many studies have documented strong price
More informationEarnings quality and earnings management : the role of accounting accruals Bissessur, S.W.
UvA-DARE (Digital Academic Repository) Earnings quality and earnings management : the role of accounting accruals Bissessur, S.W. Link to publication Citation for published version (APA): Bissessur, S.
More informationAccounting Conservatism and the Relation Between Returns and Accounting Data
Review of Accounting Studies, 9, 495 521, 2004 Ó 2004 Kluwer Academic Publishers. Manufactured in The Netherlands. Accounting Conservatism and the Relation Between Returns and Accounting Data PETER EASTON*
More informationThe Role of Credit Ratings in the. Dynamic Tradeoff Model. Viktoriya Staneva*
The Role of Credit Ratings in the Dynamic Tradeoff Model Viktoriya Staneva* This study examines what costs and benefits of debt are most important to the determination of the optimal capital structure.
More informationEvaluating the accrual-fixation hypothesis as an explanation for the accrual anomaly
Evaluating the accrual-fixation hypothesis as an explanation for the accrual anomaly Tzachi Zach * Olin School of Business Washington University in St. Louis St. Louis, MO 63130 Tel: (314)-9354528 zach@olin.wustl.edu
More informationManagerial compensation and the threat of takeover
Journal of Financial Economics 47 (1998) 219 239 Managerial compensation and the threat of takeover Anup Agrawal*, Charles R. Knoeber College of Management, North Carolina State University, Raleigh, NC
More informationHow Well Do Investors Understand Loss Persistence?
How Well Do Investors Understand Loss Persistence? Kevin Ke Li* First version: December 2008 This version: September 2010 Abstract: This paper examines investors' expectations of loss persistence. I develop
More informationA Synthesis of Accrual Quality and Abnormal Accrual Models: An Empirical Implementation
A Synthesis of Accrual Quality and Abnormal Accrual Models: An Empirical Implementation Jinhan Pae a* a Korea University Abstract Dechow and Dichev s (2002) accrual quality model suggests that the Jones
More informationDIVIDEND POLICY AND THE LIFE CYCLE HYPOTHESIS: EVIDENCE FROM TAIWAN
The International Journal of Business and Finance Research Volume 5 Number 1 2011 DIVIDEND POLICY AND THE LIFE CYCLE HYPOTHESIS: EVIDENCE FROM TAIWAN Ming-Hui Wang, Taiwan University of Science and Technology
More informationElisabetta Basilico and Tommi Johnsen. Disentangling the Accruals Mispricing in Europe: Is It an Industry Effect? Working Paper n.
Elisabetta Basilico and Tommi Johnsen Disentangling the Accruals Mispricing in Europe: Is It an Industry Effect? Working Paper n. 5/2014 April 2014 ISSN: 2239-2734 This Working Paper is published under
More informationInvestment and Financing Constraints
Investment and Financing Constraints Nathalie Moyen University of Colorado at Boulder Stefan Platikanov Suffolk University We investigate whether the sensitivity of corporate investment to internal cash
More informationEstimation and empirical properties of a firm-year measure of accounting conservatism
Estimation and empirical properties of a firm-year measure of accounting conservatism The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters.
More informationCEO Cash Compensation and Earnings Quality
CEO Cash Compensation and Earnings Quality Item Type text; Electronic Thesis Authors Chen, Zhimin Publisher The University of Arizona. Rights Copyright is held by the author. Digital access to this material
More informationComplete Dividend Signal
Complete Dividend Signal Ravi Lonkani 1 ravi@ba.cmu.ac.th Sirikiat Ratchusanti 2 sirikiat@ba.cmu.ac.th Key words: dividend signal, dividend surprise, event study 1, 2 Department of Banking and Finance
More informationAsymmetric timeliness of earnings, market-to-book and. conservatism in financial reporting
Asymmetric timeliness of earnings, market-to-book and conservatism in financial reporting Sugata Roychowdhury MIT Ross L. Watts University of Rochester Abstract In a regression of earnings on returns,
More informationAmir Sajjad Khan. 1. Introduction. order to. accrual. is used is simply. reflect. the asymmetric 2009). School of
The Asian Journal of Technology Management Vol. 6 No. 1 (2013): 49-55 Earnings Management and Stock Market Return: An Investigation of Lean Against The Wind Hypothesis Amir Sajjad Khan International Islamic
More informationLiquidity skewness premium
Liquidity skewness premium Giho Jeong, Jangkoo Kang, and Kyung Yoon Kwon * Abstract Risk-averse investors may dislike decrease of liquidity rather than increase of liquidity, and thus there can be asymmetric
More informationWhat Drives the Earnings Announcement Premium?
What Drives the Earnings Announcement Premium? Hae mi Choi Loyola University Chicago This study investigates what drives the earnings announcement premium. Prior studies have offered various explanations
More informationCapital allocation in Indian business groups
Capital allocation in Indian business groups Remco van der Molen Department of Finance University of Groningen The Netherlands This version: June 2004 Abstract The within-group reallocation of capital
More informationEARNINGS MANAGEMENT AND ACCOUNTING STANDARDS IN EUROPE
EARNINGS MANAGEMENT AND ACCOUNTING STANDARDS IN EUROPE Wolfgang Aussenegg 1, Vienna University of Technology Petra Inwinkl 2, Vienna University of Technology Georg Schneider 3, University of Paderborn
More informationThe Persistent Effect of Temporary Affirmative Action: Online Appendix
The Persistent Effect of Temporary Affirmative Action: Online Appendix Conrad Miller Contents A Extensions and Robustness Checks 2 A. Heterogeneity by Employer Size.............................. 2 A.2
More informationDoes Transparency Increase Takeover Vulnerability?
Does Transparency Increase Takeover Vulnerability? Finance Working Paper N 570/2018 July 2018 Lifeng Gu University of Hong Kong Dirk Hackbarth Boston University, CEPR and ECGI Lifeng Gu and Dirk Hackbarth
More informationIndian Households Finance: An analysis of Stocks vs. Flows- Extended Abstract
Indian Households Finance: An analysis of Stocks vs. Flows- Extended Abstract Pawan Gopalakrishnan S. K. Ritadhi Shekhar Tomar September 15, 2018 Abstract How do households allocate their income across
More informationDeviations from Optimal Corporate Cash Holdings and the Valuation from a Shareholder s Perspective
Deviations from Optimal Corporate Cash Holdings and the Valuation from a Shareholder s Perspective Zhenxu Tong * University of Exeter Abstract The tradeoff theory of corporate cash holdings predicts that
More informationCEO Tenure and Earnings Quality
CEO Tenure and Earnings Quality Weining Zhang School of Management University of Texas at Dallas Email: wxz041000@utdallas.edu December 30 th, 2009 Abstract This study investigates the relation between
More informationJ. Account. Public Policy
J. Account. Public Policy 28 (2009) 16 32 Contents lists available at ScienceDirect J. Account. Public Policy journal homepage: www.elsevier.com/locate/jaccpubpol The value relevance of R&D across profit
More informationRisk Taking and Performance of Bond Mutual Funds
Risk Taking and Performance of Bond Mutual Funds Lilian Ng, Crystal X. Wang, and Qinghai Wang This Version: March 2015 Ng is from the Schulich School of Business, York University, Canada; Wang and Wang
More informationThe predictive power of investment and accruals
The predictive power of investment and accruals Jonathan Lewellen Dartmouth College and NBER jon.lewellen@dartmouth.edu Robert J. Resutek Dartmouth College robert.j.resutek@dartmouth.edu This version:
More informationThe Effect of Matching on Firm Earnings Components
Scientific Annals of Economics and Business 64 (4), 2017, 513-524 DOI: 10.1515/saeb-2017-0033 The Effect of Matching on Firm Earnings Components Joong-Seok Cho *, Hyung Ju Park ** Abstract Using a sample
More informationReal Estate Ownership by Non-Real Estate Firms: The Impact on Firm Returns
Real Estate Ownership by Non-Real Estate Firms: The Impact on Firm Returns Yongheng Deng and Joseph Gyourko 1 Zell/Lurie Real Estate Center at Wharton University of Pennsylvania Prepared for the Corporate
More informationDo Investors Fully Understand the Implications of the Persistence of Revenue and Expense Surprises for Future Prices?
Do Investors Fully Understand the Implications of the Persistence of Revenue and Expense Surprises for Future Prices? Narasimhan Jegadeesh Dean s Distinguished Professor Goizueta Business School Emory
More informationHeterogeneous Institutional Investors and Earnings Smoothing
Heterogeneous Institutional Investors and Earnings Smoothing Yudan Zheng Long Island University This paper examines the relationship between institutional ownership and earnings smoothing by taking into
More informationRevisiting Idiosyncratic Volatility and Stock Returns. Fatma Sonmez 1
Revisiting Idiosyncratic Volatility and Stock Returns Fatma Sonmez 1 Abstract This paper s aim is to revisit the relation between idiosyncratic volatility and future stock returns. There are three key
More informationMERGERS AND ACQUISITIONS: THE ROLE OF GENDER IN EUROPE AND THE UNITED KINGDOM
) MERGERS AND ACQUISITIONS: THE ROLE OF GENDER IN EUROPE AND THE UNITED KINGDOM Ersin Güner 559370 Master Finance Supervisor: dr. P.C. (Peter) de Goeij December 2013 Abstract Evidence from the US shows
More informationThe Effect of Financial Constraints, Investment Policy and Product Market Competition on the Value of Cash Holdings
The Effect of Financial Constraints, Investment Policy and Product Market Competition on the Value of Cash Holdings Abstract This paper empirically investigates the value shareholders place on excess cash
More informationErrors in Estimating Unexpected Accruals in the Presence of. Large Changes in Net External Financing
Errors in Estimating Unexpected Accruals in the Presence of Large Changes in Net External Financing Yaowen Shan (University of Technology, Sydney) Stephen Taylor* (University of Technology, Sydney) Terry
More informationThe Relevance of the Value Relevance Literature for Financial Accounting Standard Setting
University of Pennsylvania ScholarlyCommons Finance Papers Wharton Faculty Research 9-2001 The Relevance of the Value Relevance Literature for Financial Accounting Standard Setting Robert W. Holthausen
More informationCash holdings determinants in the Portuguese economy 1
17 Cash holdings determinants in the Portuguese economy 1 Luísa Farinha Pedro Prego 2 Abstract The analysis of liquidity management decisions by firms has recently been used as a tool to investigate the
More informationMeasuring Intangible Investment
Measuring Intangible Investment THE BOUNDARIES OF FINANCIAL REPORTING AND HOW TO EXTEND THEM by Baruch Lev Philip Bardes Professor of Accounting and Finance Stern School of Business, New York University
More informationThe cross section of expected stock returns
The cross section of expected stock returns Jonathan Lewellen Dartmouth College and NBER This version: March 2013 First draft: October 2010 Tel: 603-646-8650; email: jon.lewellen@dartmouth.edu. I am grateful
More informationServicing Assets and Gain-On-Securitization under SFAS 156. Abstract
Servicing Assets and Gain-On-Securitization under SFAS 156 Abstract SFAS No. 156 was issued in 2006 to amend SFAS No.140 which addresses the accounting for servicing of financial assets and requires fair
More information1. Logit and Linear Probability Models
INTERNET APPENDIX 1. Logit and Linear Probability Models Table 1 Leverage and the Likelihood of a Union Strike (Logit Models) This table presents estimation results of logit models of union strikes during
More informationRegulation and Accounting Conservatism
Regulation and Accounting Conservatism Steven S. Crawford, Richard A. Price, Brian R. Rountree* Jones Graduate School of Business, Rice University April 2011 Abstract This study documents an increase in
More informationValuation of tax expense
Valuation of tax expense Jacob Thomas Yale University School of Management (203) 432-5977 jake.thomas@yale.edu Frank Zhang Yale University School of Management (203) 432-7938 frank.zhang@yale.edu August
More informationR&D and Stock Returns: Is There a Spill-Over Effect?
R&D and Stock Returns: Is There a Spill-Over Effect? Yi Jiang Department of Finance, California State University, Fullerton SGMH 5160, Fullerton, CA 92831 (657)278-4363 yjiang@fullerton.edu Yiming Qian
More informationA Replication Study of Ball and Brown (1968): Comparative Analysis of China and the US *
DOI 10.7603/s40570-014-0007-1 66 2014 年 6 月第 16 卷第 2 期 中国会计与财务研究 C h i n a A c c o u n t i n g a n d F i n a n c e R e v i e w Volume 16, Number 2 June 2014 A Replication Study of Ball and Brown (1968):
More informationEarly Evidence on the Determinants of Unrecognized Tax Benefits. Richard Cazier University of Iowa. Sonja Rego University of Iowa
Early Evidence on the Determinants of Unrecognized Tax Benefits Richard Cazier University of Iowa Sonja Rego University of Iowa Xiaoli Tian University of Iowa Ryan Wilson University of Iowa September 14,
More informationHow do serial acquirers choose the method of payment? ANTONIO J. MACIAS Texas Christian University. P. RAGHAVENDRA RAU University of Cambridge
How do serial acquirers choose the method of payment? ANTONIO J. MACIAS Texas Christian University P. RAGHAVENDRA RAU University of Cambridge ARIS STOURAITIS Hong Kong Baptist University August 2012 Abstract
More informationClassification Shifting in the Income-Decreasing Discretionary Accrual Firms
Classification Shifting in the Income-Decreasing Discretionary Accrual Firms 1 Bahçeşehir University, Turkey Hümeyra Adıgüzel 1 Correspondence: Hümeyra Adıgüzel, Bahçeşehir University, Turkey. Received:
More informationDo dividends convey information about future earnings? Charles Ham Assistant Professor Washington University in St. Louis
Do dividends convey information about future earnings? Charles Ham Assistant Professor Washington University in St. Louis cham@wustl.edu Zachary Kaplan Assistant Professor Washington University in St.
More informationStock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information?
Stock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information? Yongsik Kim * Abstract This paper provides empirical evidence that analysts generate firm-specific
More informationSources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As
Sources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As Zhenxu Tong * University of Exeter Jian Liu ** University of Exeter This draft: August 2016 Abstract We examine
More informationHow Markets React to Different Types of Mergers
How Markets React to Different Types of Mergers By Pranit Chowhan Bachelor of Business Administration, University of Mumbai, 2014 And Vishal Bane Bachelor of Commerce, University of Mumbai, 2006 PROJECT
More informationThe relationship between book-tax differences and earnings growth within Indonesian manufacturing firms
The relationship between book-tax differences and earnings growth within Indonesian manufacturing firms Waluyo Graduate Program in Accounting Studies, Mercu Buana University, Indonesia Abstract Previous
More informationIssues arising with the implementation of AASB 139 Financial Instruments: Recognition and Measurement by Australian firms in the gold industry
Issues arising with the implementation of AASB 139 Financial Instruments: Recognition and Measurement by Australian firms in the gold industry Abstract This paper investigates the impact of AASB139: Financial
More informationMERGER ANNOUNCEMENTS AND MARKET EFFICIENCY: DO MARKETS PREDICT SYNERGETIC GAINS FROM MERGERS PROPERLY?
MERGER ANNOUNCEMENTS AND MARKET EFFICIENCY: DO MARKETS PREDICT SYNERGETIC GAINS FROM MERGERS PROPERLY? ALOVSAT MUSLUMOV Department of Management, Dogus University. Acıbadem 81010, Istanbul / TURKEY Tel:
More informationMarket Overreaction to Bad News and Title Repurchase: Evidence from Japan.
Market Overreaction to Bad News and Title Repurchase: Evidence from Japan Author(s) SHIRABE, Yuji Citation Issue 2017-06 Date Type Technical Report Text Version publisher URL http://hdl.handle.net/10086/28621
More informationDividend Changes and Future Profitability
THE JOURNAL OF FINANCE VOL. LVI, NO. 6 DEC. 2001 Dividend Changes and Future Profitability DORON NISSIM and AMIR ZIV* ABSTRACT We investigate the relation between dividend changes and future profitability,
More informationYale ICF Working Paper No March 2003
Yale ICF Working Paper No. 03-07 March 2003 CONSERVATISM AND CROSS-SECTIONAL VARIATION IN THE POST-EARNINGS- ANNOUNCEMENT-DRAFT Ganapathi Narayanamoorthy Yale School of Management This paper can be downloaded
More informationMarket Variables and Financial Distress. Giovanni Fernandez Stetson University
Market Variables and Financial Distress Giovanni Fernandez Stetson University In this paper, I investigate the predictive ability of market variables in correctly predicting and distinguishing going concern
More informationHow Do Firms Finance Large Cash Flow Requirements? Zhangkai Huang Department of Finance Guanghua School of Management Peking University
How Do Firms Finance Large Cash Flow Requirements? Zhangkai Huang Department of Finance Guanghua School of Management Peking University Colin Mayer Saïd Business School University of Oxford Oren Sussman
More informationEvidence of conditional conservatism: fact or artifact? Panos N. Patatoukas Yale University
Evidence of conditional conservatism: fact or artifact? Panos N. Patatoukas Yale University panagiotis.patatoukas@yale.edu Jacob Thomas Yale University jake.thomas@yale.edu Current Version: October 5,
More informationSwitching Monies: The Effect of the Euro on Trade between Belgium and Luxembourg* Volker Nitsch. ETH Zürich and Freie Universität Berlin
June 15, 2008 Switching Monies: The Effect of the Euro on Trade between Belgium and Luxembourg* Volker Nitsch ETH Zürich and Freie Universität Berlin Abstract The trade effect of the euro is typically
More informationFREE CASH FLOW DISCLOSURE IN EARNINGS ANNOUNCEMENTS. Katharine Adame, Jennifer Koski, and Sarah McVay University of Washington
FREE CASH FLOW DISCLOSURE IN EARNINGS ANNOUNCEMENTS Katharine Adame, Jennifer Koski, and Sarah McVay University of Washington Background In recent years, more companies have been disclosing free cash flow
More informationPersonal Dividend and Capital Gains Taxes: Further Examination of the Signaling Bang for the Buck. May 2004
Personal Dividend and Capital Gains Taxes: Further Examination of the Signaling Bang for the Buck May 2004 Personal Dividend and Capital Gains Taxes: Further Examination of the Signaling Bang for the Buck
More informationDoes R&D Influence Revisions in Earnings Forecasts as it does with Forecast Errors?: Evidence from the UK. Seraina C.
Does R&D Influence Revisions in Earnings Forecasts as it does with Forecast Errors?: Evidence from the UK Seraina C. Anagnostopoulou Athens University of Economics and Business Department of Accounting
More informationCorporate Leverage and Taxes around the World
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-1-2015 Corporate Leverage and Taxes around the World Saralyn Loney Utah State University Follow this and
More informationAn Extended Examination of the Effectiveness of the Sarbanes Oxley Act in Reducing Pension Expense Manipulation
An Extended Examination of the Effectiveness of the Sarbanes Oxley Act in Reducing Pension Expense Manipulation Paula Diane Parker University of Southern Mississippi Nancy J. Swanson Valdosta State University
More informationThe Shiller CAPE Ratio: A New Look
The Shiller CAPE Ratio: A New Look by Jeremy J. Siegel Russell E. Professor of Finance The Wharton School University of Pennsylvania May 2013. This work is preliminary and cannot be quoted without author
More informationPremium Timing with Valuation Ratios
RESEARCH Premium Timing with Valuation Ratios March 2016 Wei Dai, PhD Research The predictability of expected stock returns is an old topic and an important one. While investors may increase expected returns
More informationPrivate Equity Performance: What Do We Know?
Preliminary Private Equity Performance: What Do We Know? by Robert Harris*, Tim Jenkinson** and Steven N. Kaplan*** This Draft: September 9, 2011 Abstract We present time series evidence on the performance
More informationHas Persistence Persisted in Private Equity? Evidence From Buyout and Venture Capital Funds
Has Persistence Persisted in Private Equity? Evidence From Buyout and Venture Capital s Robert S. Harris*, Tim Jenkinson**, Steven N. Kaplan*** and Ruediger Stucke**** Abstract The conventional wisdom
More informationAnother Look at Market Responses to Tangible and Intangible Information
Critical Finance Review, 2016, 5: 165 175 Another Look at Market Responses to Tangible and Intangible Information Kent Daniel Sheridan Titman 1 Columbia Business School, Columbia University, New York,
More informationThe Persistence and Pricing of the Cash Component of Earnings
The Rodney L. White Center for Financial Research The Persistence and Pricing of the Cash Component of Earnings Patricia M. Dechow Scott A. Richardson Richard G. Sloan -5 The Persistence and Pricing of
More informationINVESTIGATING THE EFFICACY OF BASU S DIFFERENTIAL TIMELINESS MODEL IN EVALUATING CONSERVATISM
INVESTIGATING THE EFFICACY OF BASU S DIFFERENTIAL TIMELINESS MODEL IN EVALUATING CONSERVATISM *Majid Azemi and Mohammad Nasiri Mohammadabadi Department of Accounting, Islamic Azad University, Mobarakeh
More informationEARNINGS BREAKS AND EARNINGS MANAGEMENT. Keng Kevin Ow Yong. Department of Business Administration Duke University.
EARNINGS BREAKS AND EARNINGS MANAGEMENT by Keng Kevin Ow Yong Department of Business Administration Duke University Date: Approved: Katherine Schipper, Supervisor Deborah DeMott Shane Dikolli Per Olsson
More informationThe Measurement of Speculative Investing Activities. and Aggregate Stock Returns
The Measurement of Speculative Investing Activities and Aggregate Stock Returns Asher Curtis University of Washington abcurtis@uw.edu Hyung Il Oh University of Washington-Bothell hioh@uw.edu First Draft:
More informationCan Hedge Funds Time the Market?
International Review of Finance, 2017 Can Hedge Funds Time the Market? MICHAEL W. BRANDT,FEDERICO NUCERA AND GIORGIO VALENTE Duke University, The Fuqua School of Business, Durham, NC LUISS Guido Carli
More informationCAPITAL STRUCTURE AND THE 2003 TAX CUTS Richard H. Fosberg
CAPITAL STRUCTURE AND THE 2003 TAX CUTS Richard H. Fosberg William Paterson University, Deptartment of Economics, USA. KEYWORDS Capital structure, tax rates, cost of capital. ABSTRACT The main purpose
More informationAdjusting for earnings volatility in earnings forecast models
Uppsala University Department of Business Studies Spring 14 Bachelor thesis Supervisor: Joachim Landström Authors: Sandy Samour & Fabian Söderdahl Adjusting for earnings volatility in earnings forecast
More informationFE670 Algorithmic Trading Strategies. Stevens Institute of Technology
FE670 Algorithmic Trading Strategies Lecture 4. Cross-Sectional Models and Trading Strategies Steve Yang Stevens Institute of Technology 09/26/2013 Outline 1 Cross-Sectional Methods for Evaluation of Factor
More informationIs Residual Income Really Uninformative About Stock Returns?
Preliminary and Incomplete Please do not cite Is Residual Income Really Uninformative About Stock Returns? by Sudhakar V. Balachandran* and Partha Mohanram* October 25, 2006 Abstract: Prior research found
More informationThe Changing Landscape of Accrual Accounting
DOI: 10.1111/1475-679X.12100 Journal of Accounting Research Vol. 54 No. 1 March 2016 Printed in U.S.A. The Changing Landscape of Accrual Accounting ROBERT M. BUSHMAN, ALINA LERMAN, AND X. FRANK ZHANG Received
More informationConservative Financial Reporting in Family Firms * Shuping Chen University of Washington
Conservative Financial Reporting in Family Firms * Shuping Chen shupingc@u.washington.edu University of Washington Xia Chen xia.chen@sauder.ubc.ca University of British Columbia Qiang Cheng qiang.cheng@sauder.ubc.ca
More informationSome Initial Evidence on the Role of Accounting Earnings in the Bond Market
Some Initial Evidence on the Role of Accounting Earnings in the Bond Market Peter Easton Steven Monahan Florin Vasvari Financial Statement Analysis & Valuation Conference Yountville April 2007 Motivation
More informationWhy Are Losses Less Persistent Than Profits? Curtailments versus Conservatism
Why Are Losses Less Persistent Than Profits? Curtailments versus Conservatism Alastair Lawrence lawrence@haas.berkeley.edu Richard Sloan richard_sloan@haas.berkeley.edu Haas School of Business University
More informationAccruals and Value/Glamour Anomalies: The Same or Related Phenomena?
Accruals and Value/Glamour Anomalies: The Same or Related Phenomena? Gary Taylor Culverhouse School of Accountancy, University of Alabama, Tuscaloosa AL 35487, USA Tel: 1-205-348-4658 E-mail: gtaylor@cba.ua.edu
More informationBalance Sheet Conservatism and Debt Contracting
Balance Sheet Conservatism and Debt Contracting Jayanthi Sunder a Shyam V. Sunder b Jingjing Zhang c Kellogg School of Management Northwestern University April 2009 a Northwestern University, 6245 Jacobs
More informationEarnings Management Via Intraperiod Tax Allocations: The Case of Discontinued Operations
Earnings Management Via Intraperiod Tax Allocations: The Case of Discontinued Operations Steven E. Kaplan David G. Kenchington Brian S. Wenzel Arizona State University August 20, 2015 Abstract We examine
More informationDo Investors Value Dividend Smoothing Stocks Differently? Internet Appendix
Do Investors Value Dividend Smoothing Stocks Differently? Internet Appendix Yelena Larkin, Mark T. Leary, and Roni Michaely April 2016 Table I.A-I In table I.A-I we perform a simple non-parametric analysis
More informationEli Amir ab, Eti Einhorn a & Itay Kama a a Recanati Graduate School of Business Administration,
This article was downloaded by: [Tel Aviv University] On: 18 December 2013, At: 02:20 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer
More informationEarnings Announcement Idiosyncratic Volatility and the Crosssection
Earnings Announcement Idiosyncratic Volatility and the Crosssection of Stock Returns Cameron Truong Monash University, Melbourne, Australia February 2015 Abstract We document a significant positive relation
More informationThe Persistence of Cash Flow Components into Future Cash Flows
The Persistence of Cash Flow Components into Future Cash Flows C. S. Agnes Cheng * Securities Exchange Commission, Washington, DC University of Houston, Houston, Texas 77204-4852 CHENGA@SEC.GOV Dana Hollie
More information